Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/sethgammon/citadel/daemonnpx skills add SethGammon/Citadel --skill daemongit clone --depth 1 https://github.com/SethGammon/CitadelWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00069 | $0.04135 |
| Opus 5 | $0.00034 | $0.02067 |
| Sonnet 5 | $0.00014 | $0.00827 |
| Haiku 4.5 | $0.00007 | $0.00413 |
Grade A, and why
daemon scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 268 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/daemon -- Continuous Autonomous Operation
Architecture, daemon.json field reference, and rationale: docs/DAEMON.md.
Orientation
Use when: running campaigns overnight or unattended -- chains sessions automatically until a ceiling or budget is hit. Don't use when: a single autonomous session is enough (use /archon); you want manual control between cycles (use /loop).
Default execution path (READ FIRST)
/daemon start does NOT call RemoteTrigger by default. The local runner is the default. Only pass --remote to use Anthropic's routine system, and only after explicit user confirmation.
Why: RemoteTrigger counts against the account-wide 15 routine runs / 24h cap. A single overnight run can exhaust the quota and pause every other routine on the account (including unrelated ones). See docs/ROUTINE-QUOTA.md.
Default flow — /daemon start (no --remote flag)
- Do Steps 1, 2, and 4 below (validate, check existing, write
daemon.json). - Skip Step 3 — do NOT create any
RemoteTrigger. LeavechainTriggerIdandwatchdogTriggerIdasnullin the state file. - Instead of Step 5's trigger-confirmation, output the local-runner instructions (full text: docs/DAEMON.md#local-runner-default): the state file path, campaign, and budget, then:
To start the tick loop, run in a separate terminal: npm run daemon:local Leave that terminal open. It spawns `claude -p "/do continue"` each session, respects daemon.json status, and consumes zero Anthropic routine quota. Stop with Ctrl+C or `/daemon stop`. For true unattended background operation (machine sleeps, user away): /daemon start --remote (uses RemoteTrigger, counts against 15/day cap)
Codex automation lane
In Codex, prefer a Codex Automation for durable unattended daemon ticks when available: node scripts/codex-automation.js plan --type daemon --command "/daemon tick" --cadence "<interval>" --target background-worktree --write. Use the returned prompt in the Codex app automation surface. Each run must still read and update .planning/daemon.json; Codex owns the scheduling, Citadel owns the budget/status gates and run log.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 268 lines · 69 tokens per session scan A 65c227b7dfdc
daemon is a skill published in the GitHub repository SethGammon/Citadel (912 stars, last pushed 4d ago), licensed MIT. It adds 69 tokens to every session and 4,135 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
debrief
This skill should be used when the user asks to "debrief", "record what happened", "session summary", "write a debrief", or wants to capture session activity (commits, task state changes, decisions, issues) into a structured record for the next session.
refit
This skill should be used when the user asks to "refit a workflow", "upgrade a workflow", "update workflow scaffolding", or wants to bring an existing workflow's scaffolding files up to date with the current Spacedock version.
fo-dispatch-recovery
Claude dispatch failure recovery — Break-Glass Manual Dispatch (the manual Agent() template) and Context Budget Failure/Dead Ensign Handling (the budget-unavailable stderr conditions, the recovery clause, dead-ensign bookkeeping). Read ONLY at its resident triggers inside claude-fo-dispatch.md — a non-zero or…
present-gate
First-officer gate-presentation rendering — the captain-facing gate-review template and assembly rules, including workflow-owned finding labels. Invoke at the gate point after the FO has decided a stage must be presented.
fo-status-viewer
First-officer status query/mutate/display surface — the status command flag docs, --set field docs, canonical captain-facing invocations, the Captain-Facing State Display rendering, and the GitHub-issue-filing approval gate. Invoke at the first ad-hoc status question, --set mutation, --next-id/--resolve lookup, or…
agent-workflow-playbook
AI Agent Workflow & Skill Architecture Guide — turn expert work into measurable, reusable agent systems. Covers workflow discovery, skill decomposition, harness design, evaluation, human escalation, observability, cost control, and multi-agent orchestration. Includes a measured marketing-delivery case: 15 people × 3–4…